Autonomous Training for Long-Term Spaceflight

This project will develop the autonomous capability to intelligently select/generate practice scenarios in order to provide individually targeted crew training when needed on long-duration missions. The ROBoT simulator contains a track-and-capture analysis capability which analyzes crew performance on several attributes of simulated SSRMS visiting vehicle capture tasks. Using this scoring capability as a baseline, the project will implement instructional design feedback from ROBO instructors and develop algorithms and data to provide automation of the performance evaluation, and scenario selection tasks, as well as perform longer term lesson planning required for long-duration missions.

Potential savings of crew time and training hours for the ISS Program. Potential reduction of risk to the Free Flyer Capture operation. Lessons learned can be applied to future deep space training operations with time delay.

This is early/mid-stage (TRL 6) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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